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# Abnormal-Human-Activity-Detection With the increase in the amount of anti-social activities taking place in the environment, security has been given the utmost importance lately. Therefore, organizations require a constant monitoring of people and their interactions. Since this constant monitoring of data by humans to judge if the events are abnormal is a near impossible task as it requires a lot of workforce and constant attention. Therefore, the challenge that comes up is the demand for an automatic and intelligent analysis for such video sequences. Our project comes forward as an attempt to provide solution to such a problem as the model developed is a smart surveillance system which can detect unusual or abnormal activity automatically. A method for representing the motion characteristics is described for detection and localization of unusual activities in the crowd scenes on a generalized framework which includes both a local and global range for detection of such activities.
# Customer-Analytics-and-Behaviour-Prediction Customer relationship management is one the most significant managerial tasks in organizations. Many companies may usually adopt a strategy that is known as target marketing. The marketing managers who may consider using target marketing will usually break the market down into groups and to target the most profitable segments. The current challenge is the effective utilisation of the data in CRM processes and selection of appropriate data analytics techniques. Hence, a prerequisite for the development of this customer-centric strategy is the specification of the target markets that the companies will attempt to serve. Therefore, this project comes forward as solution that begins by the Customer analysis which requires splitting up the customers into various segments that helps us in extracting the most profitable ones i.e. the loyal customers and then predicting their purchasing behaviour based on their past purchases.
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